Quality Assurance Checks

Q: Do reviewers still need to check every item?

Reviewers focus only on complex exceptions and edge cases flagged by the automation. Routine items that pass all checks are routed automatically, freeing reviewer time for higher-value work.

Q: How does the automation handle items that fail QA?

Failed items are routed back to the originator with a structured report listing each issue, its location, and why it failed. This clarity reduces rework cycles and speeds resubmission.

Q: Can the automation work with our existing tools?

Yes, the automation integrates with spreadsheets, CRMs, and notification platforms you already use. It pulls work items from your repository and sends results through your preferred communication channels.

Q: How are QA metrics tracked and reported?

All QA decisions, pass/fail counts, issue categories, and turnaround times are logged automatically. Managers access real-time dashboards instead of compiling weekly spreadsheets.

Automated QA keeps every outsourced admin output reviewed, scored, and corrected before it causes a downstream problem.

204 hrs

Manual time identified

Companies have mapped

Map This Automation

About This Automation

Quality assurance reviewers manually check each completed work item against data accuracy, compliance, and formatting standards. This process is slow and error-prone, consuming significant time on repetitive validation tasks.

Automation applies consistent rules to validate data fields, check compliance requirements, and route items automatically. Reviewers focus only on complex exceptions, while routine checks complete in seconds.

Key features:

Validate data fields against schema and format requirements automatically

Check compliance with company standards and regulatory rules in real time

Generate structured issue reports with specific failure reasons and locations

Route approved items to delivery and failed items back to originators instantly

Track QA metrics and pass/fail rates without manual spreadsheet updates

Data insights How it works Apps used What you get FAQ

Top friction points when done manually

The issues teams report most often with this process

#	Friction point	Companies Report This
1	Manual data field comparison Reviewers spend 8 minutes per item manually comparing fields against source documents, introducing typos and inconsistencies.	80%
2	Vague issue documentation Issue notes are often incomplete or unclear, forcing rework originators to guess what failed and why.	67%
3	Manual routing delays Email and status-update routing causes 1-2 day delays before rework originators or delivery teams receive items.	53%
4	Weekly metric compilation Managers spend 10 minutes weekly updating pass/fail counts and issue categories in spreadsheets, creating reporting bottlenecks.	40%
5	Compliance rule inconsistency Different reviewers apply compliance standards differently, leading to items passing QA that later fail client acceptance.	26%

Disclaimer

Automation readiness

How well-suited this process is for automation

Process Pain Score™

8.8/ 10

AI Fit Rating™

9.1/ 10

Automation Lift Index™

8.7/ 10

Hidden Overhead™

7.3/ 10

How The Automation Works

The full workflow, from trigger to completion.

1. Work Item Submitted to QAtrigger

A completed work item is marked ready for QA and enters the automation queue. The trigger pulls the item ID, content, and metadata.

2. Extract and Validate Data Fields

The automation reads the work item and checks each data field against the defined schema. It flags missing, malformed, or out-of-range values automatically.

3. Run Compliance Rules Engine

The automation applies predefined compliance and formatting rules. It checks tone, structure, branding consistency, and regulatory requirements without human input.

4. All Checks Passed?

The automation evaluates whether the item passed all data and compliance checks. If yes, it proceeds to approval. If no, it routes to rework.

5. Log Issues and Route to Rework

For failed items, the automation creates a structured issue report with specific field names and rule violations. It sends the item back to the originator with clear instructions.

6. Approve and Notify for Delivery

For passed items, the automation updates the status to approved and sends a notification to the delivery team. A summary is logged for audit purposes.

7. Update QA Metrics Dashboard

The automation records pass/fail counts, issue categories, and turnaround time in a live dashboard. Metrics are updated in real time.

Most popular tool stack used

— the complete tool combinations companies use

48% of companies

32% of companies

15% of companies

Disclaimer

What you get when you map this process

Everything you need to understand, plan, and build your automation.

ROI and business case

What this process costs today and what changes once it's automated.

Launch schedule

What gets built, in what order, and what success looks like once it's live.

Process runbook

How the automation runs day to day, including exceptions and human decision points.

Developer handover pack

Full build spec, logic, and configuration — ready to hand off without a briefing call.

Integration and connections guide

Every tool connection, credential, and data mapping the build needs.

Test and QA plan

368 hrsIdentified

4Mapped

View

Frequently asked questions

Everything you need to know before mapping this process.

What types of data errors does the automation catch?

The automation validates data types, formats, missing fields, typos, and compliance with company standards and regulatory rules. It applies the same rules consistently to every item, eliminating reviewer variation.

Do reviewers still need to check every item?

How does the automation handle items that fail QA?

Can the automation work with our existing tools?

How are QA metrics tracked and reported?

View more FAQs

Process pain:8.8/10

Mapped by:4 Companies

Map this to your business to get your exact numbers.

Map This Automation

No credit card required. It's free.

Page updated 10 August 2026